Cloud-Integrated AI Framework for Transaction-Aware Decision Optimization in Agile Healthcare Project Management
DOI:
https://doi.org/10.15680/IJCTECE.2023.0601004Keywords:
AI-driven project analytics, cloud-based healthcare management, Agile project optimization, transaction-aware decision-making, intelligent workflow monitoring, predictive risk assessment, healthcare project lifecycleAbstract
Healthcare projects increasingly require rapid decision-making, transparent communication, and adaptive coordination, especially in environments governed by Agile methodologies. This paper introduces a Cloud-Integrated AI Framework designed to enhance transaction-aware decision optimization across Agile healthcare project lifecycles. The proposed architecture leverages cloud-native analytics, intelligent workflow monitoring, and real-time transaction tracking to improve visibility, accuracy, and operational responsiveness. AI models evaluate task dependencies, clinical process flows, and transactional events to predict bottlenecks, prioritize backlog items, and recommend evidence-driven sprint planning strategies. Integrated decision engines support continuous risk assessment, quality assurance, and compliance checks aligned with healthcare standards. The framework’s cloud-based scalability ensures seamless collaboration, cross-functional access to shared project data, and secure interoperability with electronic health systems. Experimental evaluation demonstrates improvements in sprint efficiency, cycle time reduction, and decision consistency. Overall, the Cloud-Integrated AI Framework delivers a robust, intelligent foundation for optimizing Agile healthcare project management through transaction-aware, data-driven decision support.
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